Challenge: DiscoGeM 2.0 is a crowdsourced, parallel corpus of 12,834 implicit discourse relations . implicit discourse relationships are highly ambiguous and can have various interpretations .
Approach: They propose a crowdsourced annotation method that can be extended to other languages . they propose to annotate 12,834 implicit discourse relations in German, German, French and Czech data .
Outcome: The proposed method can be extended to other languages and reveals that implicit relations inferred in one language may differ from those inferted in the translation.

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DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations (2022.lrec-1)

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Challenge: DiscoGeM is a crowdsourced corpus of 6,505 implicit discourse relations . the results show that a significant proportion of discourse relations are ambiguous . text genre is crucially affected by the distribution of discourse relation labels .
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Cost-Effective Discourse Annotation in the Prague Czech–English Dependency Treebank (2024.lrec-main)

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Challenge: a method for obtaining a high-quality annotation of explicit discourse relations is a resource-demanding task.
Approach: They propose a method for obtaining a high-quality annotation of explicit discourse relations in the Czech part of the Prague Czech–English Dependency Treebank.
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ISO-based Annotated Multilingual Parallel Corpus for Discourse Markers (2022.lrec-1)

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Challenge: Discourse markers carry information about the discourse structure and organization, and also signal local dependencies or epistemic stance of speaker.
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Implicit Discourse Relation Classification: We Need to Talk about Evaluation (2020.acl-main)

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Challenge: Lack of consistency in preprocessing and evaluation poses challenges to fair comparison of results in literature.
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Announcing the Prague Discourse Treebank 3.0 (2024.lrec-main)

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Challenge: PDiT 3.0 contains 21,662 discourse relations (plus 445 list relations) in 49 thousand sentences.
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Enriching a Lexicon of Discourse Connectives with Corpus-based Data (L18-1)

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Challenge: Existing annotation efforts for multiple languages have focused on discourse connectives, but we have limited it to the class of connectives marking contrast and the additional relations such connectives might convey.
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Proceedings of the Fourth Workshop on Discourse in Machine Translation (DiscoMT 2019) (D19-65)

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Challenge: . - (EN)
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Multi-Label Classification for Implicit Discourse Relation Recognition (2024.findings-acl)

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Challenge: Prior research in discourse relation recognition has treated these instances as separate examples during training, with a gold-standard prediction matching one of the labels considered correct at test time.
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Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training (2022.lrec-1)

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Challenge: Recent methods have obtained promising results by extracting relation labels from participants . obtaining linguistic annotations from novice crowdworkers is difficult . crowdsourcing allows for fast and cost-effective collection of labelled data, but because tasks need to be intuitive, crowdworker cannot be asked to perform them.
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GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion (2020.coling-main)

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Challenge: Parliamentary debates are a valuable language resource for analyzing comprehensive options in a functional, free society.
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